University of Birmingham Featured PhD Programmes
University of Sheffield Featured PhD Programmes
University of Kent Featured PhD Programmes
Birkbeck, University of London Featured PhD Programmes
University of Manchester Featured PhD Programmes

Virtual-Real Object Registration for Stable and Accurate Augmented Reality Technology

  • Full or part time
  • Application Deadline
    Thursday, January 31, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Virtual-real object registration is the core technique that underpins augmented reality (AR) technology. AR technology has many important applications. One major challenge in augmented reality technology is the stable and accurate virtual-real object registration. The challenge is due to that fact that SLAM (Simultaneous localisation and Mapping) algorithm such as KinectFusion only works on static objects, consistent slow camera motions and idea lighting conditions during image capturing. When these conditions are not met, the AR registration algorithm fails.

This research project aims at developing efficient and accurate registration algorithms for challenge AR applications, where large surface deformations of objects are the most difficult to capture, due to either complexities of dynamic motions or image capture conditions. The algorithm developed in this project will be evaluated in the context of dynamic scene such as an AR environment with moving objects and object occlusions. A computational framework will also be developed to extend the scape of applications into augmented reality games for professional training.

Specific objectives are:
1) Develop algorithms for accurate 3D surfaces identification and matching, taking into account of surface deformations by using dense image feature points and object fusion methods;
2) Evaluate and test the algorithms in terms of noise, accuracy and speed of registration in different test cases, and develop a computational framework for processing complex dynamic scenes.
3) Integrate the stereo vision with the developed AR framework for real-time dynamic scene augmentation and fusion for procedure content generation and mixed reality applications.

This project will build a body of knowledge and develop techniques in real-time augmented reality applications, especially for dynamic scene with many object occlusions such as in image-guided and robotic assisted surgery, tissue deformation (dynamic scene) and surgical instruments (object occlusions). There is a large scope for the developed algorithms and the computational framework to be applied to general mixed reality applications in creative digital industry.

How to apply:

Applications are made via our website using the Apply Online button below. If you have an enquiry about this project please contact us via the Email NOW button below, however your application will only be processed once you have submitted an application form as opposed to emailing your CV to us.

Candidates for funded PhD studentship must demonstrate outstanding qualities and be motivated to complete a PhD in 4 years.

The PhD Studentships are open to UK, EU and international students. Candidates for a PhD Studentship should demonstrate outstanding qualities and be motivated to complete a PhD in 4 years and must demonstrate:

• A 1st class honours degree and/or a relevant Master’s degree with distinction or equivalent. If English is not your first language you’ll need IELTS (Academic) score of 6.5 minimum (with a minimum 6.0 in each component).

Funding Notes

Funded candidates will receive a maintenance grant of £14,777 per year to contribute towards living expenses during the course of your research, as well as a fee waiver for 36 months.

Funded Studentships are open to both UK/EU and International students unless otherwise specified.

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully

FindAPhD. Copyright 2005-2019
All rights reserved.